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Claude visibility
Your customers may use Claude to research a problem or assess a shortlist. We test relevant questions, review how your company is described, and improve the product, service and client information buyers need to evaluate you.
Managed support starts at US$3,000/month; focused projects are scoped separately. Compare pricing and what is included.
We distinguish web-search answers from responses that do not show live sources. Where sources are available, we review their accuracy and relevance. Your plan may include clearer capability pages, supported comparisons or corrections to company profiles. Publishing more text does not force Claude to use it or change its underlying model.
An answer gives a general description but does not resolve an integration or implementation question.
| Step | What your team should expect |
|---|---|
| Investigate | Identify the exact capability in question, whether the answer uses web sources, and which product documentation supports the claim. |
| Decide | Publish the approved capability, its prerequisites and limitations on a useful product or service page. Do not claim an integration simply because a competitor offers it. |
| Check | A buyer following the source can confirm the capability and its conditions. Record sourced and unsourced Claude responses separately. |
| Avoid | This is website and discovery work, not access to or control over Claude’s model training. |
Your buyers use Claude for research and comparisons, and you want your public information to support an accurate evaluation.
Claude answers overlook a relevant capability.
Available sources contain outdated company information.
You are being offered promises about model training you cannot verify.
We record the experience tested and whether visible web sources support the answer. An answer without live sources cannot be treated as proof that a current page was retrieved. That distinction determines what we can investigate.
Buyers comparing suppliers need details about suitability, limitations and delivery. We improve those explanations on relevant pages, using approved facts rather than unsupported superlatives. Clear comparisons help people even when an AI answer changes.
Where Claude provides sources, we check what those pages say and whether the information is current. Corrections may belong on your website or in a public profile. We do not claim access to private ranking rules or model weights.
A platform-specific service should have a reason to exist in your marketing plan. We discuss whether Claude appears in your customer research or referral data before giving it priority over better-established sources of demand.
Claude is often used to analyse detailed documents and technical choices. The source material therefore needs enough substance for a careful buyer to verify it.
We test the technical, category, comparison, risk, implementation, and brand questions that can occur before a sales conversation, then record omissions, incorrect framing, and competing entities.
Documentation, service pages, research, comparisons, author biographies, dates, limitations, methodologies, and examples are reviewed for explicit facts and traceable support.
Claude findings are compared with ChatGPT, Perplexity, Gemini, Copilot, Google results, and the public company information. Conflicting facts are corrected at the source rather than rewritten separately for each model.
The questions tested and the sources actually available to inspect.
Agreed capability and comparison improvements.
Observations and referral data without blending them into other AI products.
Review the buyer use cases worth testing.
Correct supported gaps in public information.
Repeat the tests and reassess priority as useful data emerges.
A strong source defines the product, explains the use case, states limitations, names the author, and provides evidence that can be checked outside the page.
We agree the reporting with your team and distinguish completed work from business results. Missing data and other changes affecting performance stay visible.
Direct answers to the questions teams ask before deciding whether this work fits.
No. We work on public information and observable search experiences. We cannot edit model weights or promise a model update. The report states what was tested and which sources could actually be inspected.
It involves prompt research, answer monitoring, entity and source audits, detailed content improvements, credible corroboration, and cross-platform visibility reporting.
No. A company can publish clearer, current, verifiable information and correct inaccurate public sources, but it cannot guarantee a model’s wording or recommendation.
Clear documentation, direct service and product facts, original research, expert explanations, comparisons with visible criteria, and content that states limitations are strong source candidates.
No. This service improves public information and tests observable answers. It does not alter the model or guarantee that a future response will use a particular page.
Tell us about your website, customers and the problem you want to solve. We will discuss fit, responsibilities and a realistic scope before you commit.
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